Multi-scale fractal analysis of image texture and pattern

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous laud covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indic ates greater complexity as pixel size increases, a forested land cover grad ually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken f our months apart show a more complex relation between pixel size and fracta l dimension. The major visible difference between the spring and late summe r NDVI images is the absence of high elevation snow cover in the summer ima ge. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimension-resolution relation pro vides indications of how image classification or feature identification wil l be affected by changes in sensor spatial resolution.